| | |
| | | def __init__(self, **kwargs): |
| | | if not kwargs.get("disable_log", True): |
| | | tables.print() |
| | | if kwargs.get("export_model", False): |
| | | os.environ['EXPORTING_MODEL'] = 'TRUE' |
| | | |
| | | |
| | | model, kwargs = self.build_model(**kwargs) |
| | | |
| | | # if vad_model is not None, build vad model else None |
| | |
| | | device = "cpu" |
| | | kwargs["batch_size"] = 1 |
| | | kwargs["device"] = device |
| | | |
| | | if kwargs.get("ncpu", None): |
| | | torch.set_num_threads(kwargs.get("ncpu")) |
| | | |
| | | torch.set_num_threads(kwargs.get("ncpu", 4)) |
| | | |
| | | |
| | | # build tokenizer |
| | | tokenizer = kwargs.get("tokenizer", None) |
| | |
| | | calib_num: int = 100, |
| | | opset_version: int = 14, |
| | | **cfg): |
| | | os.environ['EXPORTING_MODEL'] = 'TRUE' |
| | | |
| | | device = cfg.get("device", "cpu") |
| | | model = self.model.to(device=device) |
| | | kwargs = self.kwargs |
| | | deep_update(kwargs, cfg) |
| | | kwargs["device"] = device |
| | | del kwargs["model"] |
| | | model = self.model |
| | | model.eval() |
| | | |
| | | batch_size = 1 |